TUCAN - Twitter User Centric ANalyzer

This an on-line demo version of the Dashboard visualizer from the TUCAN framework.

Poster paper accepted at The 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013).

Abstract

Twitter has attracted millions of users that generate
a humongous flow of information at constant pace. The research
community has thus started proposing tools to extract meaningful
information from tweets. In this paper, we take a different angle
from the mainstream of previous works: we explicitly target the
analysis of the timeline of tweets from “single users”. We define
a framework - named TUCAN - to compare information offered
by the target users over time, and to pinpoint recurrent topics or
topics of interest. First, tweets belonging to the same time window
are aggregated into “bird songs”. Several filtering procedures
can be selected to remove stop-words and reduce noise. Then,
each pair of bird songs is compared using a similarity score to
automatically highlight the most common terms, thus highlighting
recurrent or persistent topics. TUCAN can be naturally applied
to compare bird song pairs generated from timelines of different
users.
By showing actual results for both public profiles and
anonymous users, we show how TUCAN is useful to highlight
meaningful information from a target user’s Twitter timeline.